Nutrient Remineralization by Ramicrusta

Background

Brief Introduction:

 

The rapid proliferation of the red encrusting macroalgal Ramicrusta in the Caribbean is raising concerns about its ecological impacts, particularly its ability to outcompete foundational benthic species, inhibit invertebrate recruitment, and overgrow living coral colonies, often leading to coral mortality (Eckrich & Engel, 2013; Edmunds et al., 2019). Coral genera exhibit varying levels of susceptibility to Ramicrusta colonization, with Orbicella sp. among the most vulnerable and experiencing high alga overgrowth rates (Hollister et al., 2021; Fig. 1).

Considerable evidence illustrates Ramicrusta’s tendency to interact with and overgrow live corals (Eckrich & Engel, 2013; Ballantine et al., 2016; Edmunds et al., 2019; Hollister et al., 2021), yet there is a disconnect when it comes to understanding the factors contributing to this relationship. Macroalgal growth is typically nutrient-limited, especially in oligotrophic tropical waters (Amato et al., 2016; Strait et al., 2021). Thus, Ramicrusta may be deriving nutrients from the coral itself, fueling these interactions and promoting its own growth.

 

Fig. 1: R. textilis overgrowing an O. annularis colony (photo: Abigail Gretta).

 

Application of Stable Isotope Analysis:

Based on predictable isotope fractionation patterns (Fry, 1988), the ability of the alga to remineralize coral nutrients can be evaluated by comparing the nutrient levels in both the alga and coral tissues through bulk stable isotope analyses. Fractionation refers to the preferential use of the lighter isotope (12C, 14N) during metabolic processes, concentrating the heavier form in the organism’s tissues (13C, 15N) (Rounick & Winterbourn, 1986; Fry, 1988; Cohen & Fong, 2004). In heterotrophic consumers, the ratio of heavy to light isotopes for carbon (C) and nitrogen (N) generally enrich by 1‰ and 3‰ per trophic level, respectively (Fry, 1988). These ratios, or isotope signatures, are represented by the delta notation in parts per thousand (δ13C, δ15N). This unique aspect of isotope fractionation provides insight into a consumer’s food source (δ13C) and trophic position (δ15N) (Rounick & Winterbourn, 1986; Post et al., 2002). However, primary producers typically exhibit a lack of fractionation (Gartner et al., 2002; Cohen & Fong, 2004; Strait et al., 2021). Thus, both the C and N signatures generally reflect their source. As a result, macroalgal bioassays serve as powerful proxies for nutrient studies in oligotrophic environments because tissue analyses can trace nutrient sourcing (δ13C, δ15N), availability (C%, N%), and limitations (C:N) in the surrounding water (Amato et al., 2016; Amato et al., 2018; Strait et al., 2021).

In theory, if Ramicrusta species are remineralizing coral tissues, the C and N isotope signatures of the algae should mirror those of the coral (Cohen & Fong, 2004). Additionally, the C and N percentages may be enhanced in the alga as a result of additional coral nutrients, which would, in turn, reduce nutrient limitations and lower the C:N ratio. (Amato et al., 2016). However, baseline tissue nutrient analyses on the genus Ramicrusta are lacking; therefore, we will need to include two upright geniculate calcifying macroalgae species into our sampling to offer context into Ramicrusta’s nutrient parameters. The rhizophytic green alga Halimeda opuntia and epilithic red alga Jania adhereans will be prioritized because they are prominent calcifiers within the region and their nutrient contents have been established for oligotrophic reef systems (Fong et al., 2003; Koch et al., 2023).

The following are the preliminary methods, results, and conclusions from a pilot study conducted on September 2, 2024.

Methods

Site:

Sample collection occurred on the leeward side of Flat Cay, an offshore 9 m depth reef along the southwest side of St. Thomas, U.S. Virgin Islands (Fig. 2). This site was selected because of its high abundance of R. textilis (46.0% ± 5.9; Hollister et al., 2021) and high frequency of interactions between the alga and Orbicella annularis (personal observation). To characterize the abiotic conditions during algal and coral sampling, a temperature logger (Hobo Pendant) and PAR meter were deployed a month prior to the collection time and retrieved on the final day of sampling.

Fig. 2: Site

Alga Collection:

Open-circuit SCUBA was used for all algal collections. Replicates of each algal were randomly collected by hand, with a minimum of five meters between samples. R. textilis were brushed of epiphytes and chiseled from 10 rocks (control) and 10 O. annularis colonies. O. annularis colonies that appeared visually healthy were selected for alga collection. Two R. textilis samples were removed from each substrate (n = 20 R. textilis per substrate type), one at the margin of algal growth (n = 10) and the other at a linear distance away (2 to 3 cm) from the margin on the same contiguous algal thallus (n = 10), with distances between samples measured and photographed (Fig. 3). This sampling strategy will distinguish the alga’s nutrient parameters during direct interaction with living coral to those in non-interacting regions, with the rock samples serving as controls for both conditions. Algal replicates were placed in individual plastic bags at depth with ambient seawater. Samples were transported to the laboratory in a dark container to minimize physiological stress and processed immediately.

Fig. 3: R. textilis were collected from 10 O. annularis colonies (left) and 10 rocks (control), with marginal and non-marginal replicates sampled from each substrate type.

Lab Processing:

Macroalgae were rinsed with deionized water (DI) to remove any external contaminants (i.e., invertebrates and epiphytes) and thoroughly dried with paper towels (Strait et al., 2021). Samples were loosely parceled in combusted aluminum foil with each sample code and dried at 60℃ to constant weight in a drying oven (24-36 hours). With a clean mortar and pestle (ethanol and DI rinse between samples), algae were ground to a fine powder and carefully packaged in 1.5 mL Eppendorf tubes (Strait et al., 2021). Stable isotope analyses were processed by an Elemental Analyzer Delta V at the University of Hawai’i at Mānoa. Dual stable isotope analyses were performed because acidification has the potential to degrade \(\delta^{15}\)N and unaltering calcified tissue can skew \(\delta^{13}\)C (Strait & Spalding, 2021).

Graphs & Analyses

Data Analysis:

All data were tested for homogeneity and normality. Log transformations were used when data violated ANOVA assumptions. Tissue nutrients (\(\delta^{15}\)N, % N, and C:N) were assessed using two-factor ANOVA (factors: Substrate, Growth Region, and the interaction of the two). Tukey’s honestly significant difference post hoc test was applied to show pairwise comparisons, with distinct letters on graphs denoting significant differences.

Analysis of Variance Model

	Df	Sum Sq	Mean Sq	F value	Pr(>F)
Substrate	1	0.1896	0.1896	4.158	0.04978
Growth_Region	1	0.3313	0.3313	7.264	0.01112
Substrate:Growth_Region	1	0.08185	0.08185	1.794	0.1898
Residuals	32	1.46	0.04562	NA	NA

Analysis of Variance Model

	Df	Sum Sq	Mean Sq	F value	Pr(>F)
Substrate	1	0.49	0.49	0.8808	0.355
Growth_Region	1	8.258	8.258	14.84	0.0005287
Substrate:Growth_Region	1	1.491	1.491	2.681	0.1114
Residuals	32	17.8	0.5563	NA	NA

Analysis of Variance Model

	Df	Sum Sq	Mean Sq	F value	Pr(>F)
Substrate	1	56.95	56.95	11.05	0.00223
Growth_Region	1	0.6441	0.6441	0.125	0.726
Substrate:Growth_Region	1	0.03711	0.03711	0.007202	0.9329
Residuals	32	164.9	5.153	NA	NA

Conclusion